Abstract
As a nature inspired metaheuristic algorithm, Water Cycle Algorithm (WCA) has been applied to some real-world problems for its excellent optimization performance. However, in standard WCA, each individual only learns information from a higher level individual but lacks communication among inter peers, which leads to the loss of some important information. In order to address this problem, an inter-peer communication mechanism based Water Cycle Algorithm (IPCWCA) is presented in this paper. In IPCWCA, besides getting information from higher level individual, each stream and river communicate with one of their peers to increase the diversity of whole population and enhance the efficiency of optimization. To explore the efficiency of IPCWCA, other four heuristic algorithms are involved to test on eight benchmark functions. Experimental results show that IPCWCA performs better on solving different types of problems compared with other four algorithms.
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Acknowledgements
This work is partially supported by the Natural Science Foundation of Guangdong Province (2016A030310074), Project supported by Innovation and Entrepreneurship Research Center of Guangdong University Student (2018A073825).
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Niu, B., Liu, H., Song, X. (2019). An Inter-Peer Communication Mechanism Based Water Cycle Algorithm. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11655. Springer, Cham. https://doi.org/10.1007/978-3-030-26369-0_5
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